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Synthetic Gym Members Exercise Records Dataset
Sports & Recreation
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£179.99
About
This Synthetic Gym Members Exercise Dataset is created for educational and research purposes in fitness, public health, and data science. It provides detailed demographic, physiological, and workout-related information about gym members, enabling analysis of exercise patterns, health metrics, and fitness progress. The dataset can be utilized for building predictive models and exploring personalized workout and fitness management strategies.
Dataset Features
- Age: Age of the gym member in years.
- Gender: Biological sex of the gym member (Male/Female).
- Weight (kg): Weight of the individual in kilograms.
- Height (m): Height of the individual in meters.
- Max_BPM: Maximum heartbeats per minute during exercise.
- Avg_BPM: Average heartbeats per minute during exercise.
- Resting_BPM: Resting heartbeats per minute.
- Session_Duration (hours): Duration of the exercise session in hours.
- Calories_Burned: Total calories burned during the workout session.
- Workout_Type: Type of workout performed (e.g., HIIT, Yoga, Cardio).
- Fat_Percentage: Body fat percentage of the individual.
- Water_Intake (liters): Water intake during the workout session in liters.
- Workout_Frequency (days/week): Number of workout days per week.
- Experience_Level: Experience level of the gym member (1 = Beginner, 2 = Intermediate, 3 = Advanced).
- BMI: Body Mass Index, calculated as weight (kg) / (height (m))².
Distribution
Usage
This dataset is suited for the following applications:
- Health and Fitness Insights: Analyze relationships between BMI, workout types, and health metrics like fat percentage or heart rate.
- Personalized Exercise Plans: Develop algorithms to recommend tailored workout routines based on individual fitness levels and goals.
- Calorie Burn Prediction: Build predictive models to estimate calories burned during workout sessions based on key features.
- Public Health Research: Study exercise trends and their impact on health outcomes.
- Fitness Tracking: Use data to monitor individual or group fitness progress over time.
Coverage
This synthetic dataset is anonymized and adheres to data privacy standards. It is designed for research and learning purposes, with diverse cases representing various fitness levels, workout types, and health metrics.
License
CC0 (Public Domain)
Who Can Use It
- Data Science Practitioners: For practicing data preprocessing, regression, and classification tasks related to fitness and health.
- Fitness Professionals and Researchers: To explore trends and patterns in gym members' workout habits and health outcomes.
- Public Health Analysts: To design effective strategies promoting physical activity and healthy lifestyles.
- Policy Makers and Regulators: For data-driven decision-making to promote fitness and public health initiatives.
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